Reproduction of Large-Scale Bioreactor Conditions on Microfluidic Chips.

Ho P, Westerwalbesloh C, Kaganovitch E, Grünberger A, Neubauer P, Kohlheyer D, Lieres E von (2019)
Microorganisms 7(4): 105.

Zeitschriftenaufsatz | Veröffentlicht | Englisch
 
Download
Es wurden keine Dateien hochgeladen. Nur Publikationsnachweis!
Autor*in
Ho, Phuong; Westerwalbesloh, Christoph; Kaganovitch, Eugen; Grünberger, AlexanderUniBi; Neubauer, Peter; Kohlheyer, Dietrich; Lieres, Eric von
Abstract / Bemerkung
Microbial cells in industrial large-scale bioreactors are exposed to fluctuating conditions, e.g., nutrient concentration, dissolved oxygen, temperature, and pH. These inhomogeneities can influence the cell physiology and metabolism, e.g., decelerate cell growth and product formation. Microfluidic systems offer new opportunities to study such effects in great detail by examining responses to varying environmental conditions at single-cell level. However, the possibility to reproduce large-scale bioreactor conditions in microscale cultivation systems has not yet been systematically investigated. Hence, we apply computational fluid dynamics (CFD) simulations to analyze and compare three commonly used microfluidic single-cell trapping and cultivation devices that are based on (i) mother machines (MM), (ii) monolayer growth chambers (MGC), and (iii) negative dielectrophoresis (nDEP). Several representative time-variant nutrient concentration profiles are applied at the chip entry. Responses to these input signals within the studied microfluidic devices are comparatively evaluated at the positions of the cultivated cells. The results are comprehensively presented in a Bode diagram that illustrates the degree of signal damping depending on the frequency of change in the inlet concentration. As a key finding, the MM can accurately reproduce signal changes that occur within 1 s or slower, which are typical for the environmental conditions observed by single cells in large-scale bioreactors, while faster changes are levelled out. In contrast, the nDEP and MGC are found to level out signal changes occurring within 10 s or faster, which can be critical for the proposed application.
Erscheinungsjahr
2019
Zeitschriftentitel
Microorganisms
Band
7
Ausgabe
4
Art.-Nr.
105
ISSN
2076-2607
eISSN
2076-2607
Page URI
https://pub.uni-bielefeld.de/record/2935495

Zitieren

Ho P, Westerwalbesloh C, Kaganovitch E, et al. Reproduction of Large-Scale Bioreactor Conditions on Microfluidic Chips. Microorganisms. 2019;7(4): 105.
Ho, P., Westerwalbesloh, C., Kaganovitch, E., Grünberger, A., Neubauer, P., Kohlheyer, D., & Lieres, E. von (2019). Reproduction of Large-Scale Bioreactor Conditions on Microfluidic Chips. Microorganisms, 7(4), 105. doi:10.3390/microorganisms7040105
Ho, Phuong, Westerwalbesloh, Christoph, Kaganovitch, Eugen, Grünberger, Alexander, Neubauer, Peter, Kohlheyer, Dietrich, and Lieres, Eric von. 2019. “Reproduction of Large-Scale Bioreactor Conditions on Microfluidic Chips.”. Microorganisms 7 (4): 105.
Ho, P., Westerwalbesloh, C., Kaganovitch, E., Grünberger, A., Neubauer, P., Kohlheyer, D., and Lieres, E. von (2019). Reproduction of Large-Scale Bioreactor Conditions on Microfluidic Chips. Microorganisms 7:105.
Ho, P., et al., 2019. Reproduction of Large-Scale Bioreactor Conditions on Microfluidic Chips. Microorganisms, 7(4): 105.
P. Ho, et al., “Reproduction of Large-Scale Bioreactor Conditions on Microfluidic Chips.”, Microorganisms, vol. 7, 2019, : 105.
Ho, P., Westerwalbesloh, C., Kaganovitch, E., Grünberger, A., Neubauer, P., Kohlheyer, D., Lieres, E. von: Reproduction of Large-Scale Bioreactor Conditions on Microfluidic Chips. Microorganisms. 7, : 105 (2019).
Ho, Phuong, Westerwalbesloh, Christoph, Kaganovitch, Eugen, Grünberger, Alexander, Neubauer, Peter, Kohlheyer, Dietrich, and Lieres, Eric von. “Reproduction of Large-Scale Bioreactor Conditions on Microfluidic Chips.”. Microorganisms 7.4 (2019): 105.

42 References

Daten bereitgestellt von Europe PubMed Central.

Physiological responses to mixing in large scale bioreactors.
Enfors SO, Jahic M, Rozkov A, Xu B, Hecker M, Jurgen B, Kruger E, Schweder T, Hamer G, O'Beirne D, Noisommit-Rizzi N, Reuss M, Boone L, Hewitt C, McFarlane C, Nienow A, Kovacs T, Tragardh C, Fuchs L, Revstedt J, Friberg PC, Hjertager B, Blomsten G, Skogman H, Hjort S, Hoeks F, Lin HY, Neubauer P, van der Lans R, Luyben K, Vrabel P, Manelius A., J. Biotechnol. 85(2), 2001
PMID: 11165362
Scale-down simulators for metabolic analysis of large-scale bioprocesses.
Neubauer P, Junne S., Curr. Opin. Biotechnol. 21(1), 2010
PMID: 20185293
Fast dynamic response of the fermentative metabolism of Escherichia coli to aerobic and anaerobic glucose pulses.
Lara AR, Taymaz-Nikerel H, Mashego MR, van Gulik WM, Heijnen JJ, Ramirez OT, van Winden WA., Biotechnol. Bioeng. 104(6), 2009
PMID: 19685524
Bioprocess scale-up/down as integrative enabling technology: from fluid mechanics to systems biology and beyond.
Delvigne F, Takors R, Mudde R, van Gulik W, Noorman H., Microb Biotechnol 10(5), 2017
PMID: 28805306
Process inhomogeneity leads to rapid side product turnover in cultivation of Corynebacterium glutamicum.
Kaß F, Junne S, Neubauer P, Wiechert W, Oldiges M., Microb. Cell Fact. 13(), 2014
PMID: 24410842
Response of Corynebacterium glutamicum exposed to oscillating cultivation conditions in a two- and a novel three-compartment scale-down bioreactor.
Lemoine A, Maya Martιnez-Iturralde N, Spann R, Neubauer P, Junne S., Biotechnol. Bioeng. 112(6), 2015
PMID: 25728062
Dynamic Behavior of Microbial Populations in Stirred Bioreactors Simulated with Euler-Lagrange Methods: Traveling along the Lifelines of Single Cells
Lapin A., Müller D., Reuss M.., 2004
Euler-Lagrange computational fluid dynamics for (bio)reactor scale down: An analysis of organism lifelines.
Haringa C, Tang W, Deshmukh AT, Xia J, Reuss M, Heijnen JJ, Mudde RF, Noorman HJ., Eng. Life Sci. 16(7), 2016
PMID: 27917102
Computational fluid dynamics simulation of an industrial P. chrysogenum fermentation with a coupled 9-pool metabolic model: Towards rational scale-down and design optimization
Haringa C., Tang W., Wang G., Deshmukh A.T., van W.A., Chu J., van W.M., Heijnen J.J., Mudde R.F., Noorman H.J.., 2017
Single-cell microfluidics: opportunity for bioprocess development.
Grunberger A, Wiechert W, Kohlheyer D., Curr. Opin. Biotechnol. 29(), 2014
PMID: 24642389
Single cells in confined volumes: microchambers and microdroplets.
Hummer D, Kurth F, Naredi-Rainer N, Dittrich PS., Lab Chip 16(3), 2016
PMID: 26758781
Beyond the bulk: disclosing the life of single microbial cells.
Rosenthal K, Oehling V, Dusny C, Schmid A., FEMS Microbiol. Rev. 41(6), 2017
PMID: 29029257
Noise-driven growth rate gain in clonal cellular populations.
Hashimoto M, Nozoe T, Nakaoka H, Okura R, Akiyoshi S, Kaneko K, Kussell E, Wakamoto Y., Proc. Natl. Acad. Sci. U.S.A. 113(12), 2016
PMID: 26951676
Robustness and accuracy of cell division in Escherichia coli in diverse cell shapes.
Mannik J, Wu F, Hol FJ, Bisicchia P, Sherratt DJ, Keymer JE, Dekker C., Proc. Natl. Acad. Sci. U.S.A. 109(18), 2012
PMID: 22509007
Investigating the physiology of viable but non-culturable bacteria by microfluidics and time-lapse microscopy.
Bamford RA, Smith A, Metz J, Glover G, Titball RW, Pagliara S., BMC Biol. 15(1), 2017
PMID: 29262826
From industrial fermentor to CFD-guided downscaling: What have we learned?
Haringa C., Mudde R.F., Noorman H.J.., 2018
Long-term model predictive control of gene expression at the population and single-cell levels.
Uhlendorf J, Miermont A, Delaveau T, Charvin G, Fages F, Bottani S, Batt G, Hersen P., Proc. Natl. Acad. Sci. U.S.A. 109(35), 2012
PMID: 22893687
Monitoring single-cell gene regulation under dynamically controllable conditions with integrated microfluidics and software.
Kaiser M, Jug F, Julou T, Deshpande S, Pfohl T, Silander OK, Myers G, van Nimwegen E., Nat Commun 9(1), 2018
PMID: 29335514
Robust growth of Escherichia coli.
Wang P, Robert L, Pelletier J, Dang WL, Taddei F, Wright A, Jun S., Curr. Biol. 20(12), 2010
PMID: 20537537
Microfluidic chemostat for measuring single cell dynamics in bacteria.
Long Z, Nugent E, Javer A, Cicuta P, Sclavi B, Cosentino Lagomarsino M, Dorfman KD., Lab Chip 13(5), 2013
PMID: 23334753
A disposable picolitre bioreactor for cultivation and investigation of industrially relevant bacteria on the single cell level.
Grunberger A, Paczia N, Probst C, Schendzielorz G, Eggeling L, Noack S, Wiechert W, Kohlheyer D., Lab Chip 12(11), 2012
PMID: 22511122
Spatiotemporal microbial single-cell analysis using a high-throughput microfluidics cultivation platform.
Grunberger A, Probst C, Helfrich S, Nanda A, Stute B, Wiechert W, von Lieres E, Noh K, Frunzke J, Kohlheyer D., Cytometry A 87(12), 2015
PMID: 26348020
High-throughput gene expression analysis at the level of single proteins using a microfluidic turbidostat and automated cell tracking.
Ullman G, Wallden M, Marklund EG, Mahmutovic A, Razinkov I, Elf J., Philos. Trans. R. Soc. Lond., B, Biol. Sci. 368(1611), 2012
PMID: 23267179
Modeling and CFD simulation of nutrient distribution in picoliter bioreactors for bacterial growth studies on single-cell level.
Westerwalbesloh C, Grunberger A, Stute B, Weber S, Wiechert W, Kohlheyer D, von Lieres E., Lab Chip 15(21), 2015
PMID: 26345659
Miniaturized octupole cytometry for cell type independent trapping and analysis
Fritzsch F.S.O., Blank L.M., Dusny C., Schmid A.., 2017
Picoliter nDEP traps enable time-resolved contactless single bacterial cell analysis in controlled microenvironments.
Fritzsch FS, Rosenthal K, Kampert A, Howitz S, Dusny C, Blank LM, Schmid A., Lab Chip 13(3), 2013
PMID: 23223864
Coarse-graining bacteria colonies for modelling critical solute distributions in picolitre bioreactors for bacterial studies on single-cell level.
Westerwalbesloh C, Grunberger A, Wiechert W, Kohlheyer D, von Lieres E., Microb Biotechnol 10(4), 2017
PMID: 28371389
Beyond growth rate 0.6: What drives Corynebacterium glutamicum to higher growth rates in defined medium.
Unthan S, Grunberger A, van Ooyen J, Gatgens J, Heinrich J, Paczia N, Wiechert W, Kohlheyer D, Noack S., Biotechnol. Bioeng. 111(2), 2013
PMID: 23996851

Deen W.M.., 1998
Densities and Viscosities of Ternary Systems of Water + Glucose + Sodium Chloride at Several Temperatures
Comesaña J.F., Otero J.J., García E., Correa A.., 2003
Diffusion in Supersaturated Solutions. II. Glucose Solutions
Gladden J.K., Dole M.., 1953
The Growth of Bacterial Cultures
Monod J.., 1949
Microfluidic growth chambers with optical tweezers for full spatial single-cell control and analysis of evolving microbes.
Probst C, Grunberger A, Wiechert W, Kohlheyer D., J. Microbiol. Methods 95(3), 2013
PMID: 24041615
Monolithic microfabricated valves and pumps by multilayer soft lithography.
Unger MA, Chou HP, Thorsen T, Scherer A, Quake SR., Science 288(5463), 2000
PMID: 10753110
Microfluidic picoliter bioreactor for microbial single-cell analysis: fabrication, system setup, and operation.
Gruenberger A, Probst C, Heyer A, Wiechert W, Frunzke J, Kohlheyer D., J Vis Exp (82), 2013
PMID: 24336165
Fiji: an open-source platform for biological-image analysis.
Schindelin J, Arganda-Carreras I, Frise E, Kaynig V, Longair M, Pietzsch T, Preibisch S, Rueden C, Saalfeld S, Schmid B, Tinevez JY, White DJ, Hartenstein V, Eliceiri K, Tomancak P, Cardona A., Nat. Methods 9(7), 2012
PMID: 22743772

Yarlagadda R.R.., 2010
Diffusion coefficient measurements in microfluidic devices.
Culbertson CT, Jacobson SC, Michael Ramsey J., Talanta 56(2), 2002
PMID: 18968508
Export

Markieren/ Markierung löschen
Markierte Publikationen

Open Data PUB

Web of Science

Dieser Datensatz im Web of Science®
Quellen

PMID: 31010155
PubMed | Europe PMC

Suchen in

Google Scholar